scholarly journals Towards a Parsimonious Pathway Model of Modifiable and Mediating Risk Factors Leading to Diabetes Risk

2021 ◽  
Author(s):  
Yi-Ching Lynn Ho ◽  
Vivian Shu Yi Lee ◽  
Moon-Ho Ringo Ho ◽  
Gladis Jing Lin ◽  
Julian Thumboo
Keyword(s):  
Risk Factors ◽  
Disease Prevention ◽  
Structural Equation ◽  
Diabetes Risk ◽  
Risk Indicators ◽  
Equation Modeling ◽  
Pathway Model ◽  
Physiological Load ◽  
Modifiable Factors ◽  
Lifestyle Risk

Abstract Background: The development of diabetes mellitus has been closely linked to multiple risk factors, of which modifiable factors are of particular interest for disease prevention. Yet few studies have assessed the system of pathways though which risk factors lead to diabetes, and how the different groups of risk factors may interact,both as independent or mediating factors. Methods: We aimed to develop a broad pathway model for diabetes risk with modifiable lifestyle risk factors as the start point, hypothesising that Lifestyle Risk (physical inactivity, smoking, poor diet and insufficient sleep) would impact Diabetes Risk (HbA1c) through the mediating factor of Physiological Load (BMI, resting pulse rate, CRP, systolic and diastolic blood pressure). The lifestyle and physiological factors were grouped via principal components analysis and a summary index respectively. Non modifiable risk factors, such as sociodemographics were specified as covariates. We used structural equation modeling to test this model, first using Wave 5 data from the Indonesian Family Life Survey (IFLS), as this was the only wave that collected all indicators of interest. To fit in longitudinal data from an earlier wave (IFLS4), we further tested a smaller model with the two Lifestyle Risk indicators available. Results: Both models showed indirect effects of Lifestyle Risk on Diabetes Risk via Physiological Load, with the cross-sectional model also showing a direct effect. The effect sizes were within the range of other studies that assessed the variables separately. Conclusion: Taken together, the results support the model of an indirect effect of Lifestyle Risk on Diabetes through Physiological Load. Specifying Lifestyle Risk as an observable, composite variable incorporates the cumulative effect of risk behaviour and differentiates this study from previous studies assessing it as a latent construct. We were able to assess causality with retrospective cohort data. Finally, the parsimonious model groups and summarises the multifarious risk factors and illustrates parsimonious and modifiable pathways that could be applied in chronic disease prevention efforts.

scholarly journals Towards a Parsimonious Pathway Model of Modifiable and Mediating Risk Factors Leading to Diabetes Risk

2021 ◽  
Vol 18 (20) ◽  
pp. 10907
Author(s):  
Yi-Ching Lynn Ho ◽  
Vivian Shu Yi Lee ◽  
Moon-Ho Ringo Ho ◽  
Gladis Jing Lin ◽  
Julian Thumboo
Keyword(s):  
Risk Factors ◽  
Chronic Disease ◽  
Disease Prevention ◽  
Diabetes Risk ◽  
Chronic Disease Prevention ◽  
Equation Modeling ◽  
Modifiable Risk Factors ◽  
Pathway Model ◽  
Physiological Load ◽  
Lifestyle Risk

Modifiable risk factors are of interest for chronic disease prevention. Few studies have assessed the system of modifiable and mediating pathways leading to diabetes mellitus. We aimed to develop a pathway model for Diabetes Risk with modifiable Lifestyle Risk factors as the start point and Physiological Load as the mediator. As there are no standardised risk thresholds for lifestyle behaviour, we derived a weighted composite for Lifestyle Risk. Physiological Load was based on an index using clinical thresholds. Sociodemographics are non-modifiable risk factors and were specified as covariates. We used structural equation modeling to test the model, first using 2014/2015 data from the Indonesian Family Life Survey. Next, we fitted a smaller model with longitudinal data (2007/2008 to 2014/2015), given limited earlier data. Both models showed the indirect effects of Lifestyle Risk on Diabetes Risk via the mediator of Physiological Load, whereas the direct effect was only supported in the cross-sectional analysis. Specifying Lifestyle Risk as an observable, composite variable incorporates the cumulative effect of risk behaviour and differentiates this study from previous studies assessing it as a latent construct. The parsimonious model groups the multifarious risk factors and illustrates modifiable pathways that could be applied in chronic disease prevention efforts.

How Community and Individual Risk Factors Mutually Impact Youth’s Perceived Safety: A Syndemic Analysis Using Structural Equation Modeling

2021 ◽  
pp. 088626052110283
Author(s):  
Yingwei Yang ◽  
Karen D. Liller ◽  
Martha Coulter ◽  
Abraham Salinas-Miranda ◽  
Dinorah Martinez Tyson ◽  
...  
Keyword(s):  
Risk Factors ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Community Safety ◽  
Equation Modeling ◽  
Individual Risk ◽  
Latent Factor ◽  
Community Factors ◽  
Individual Risk Factors ◽  
Syndemic Theory

The purpose of this study was to evaluate the mutual impact of community and individual factors on youth’s perceptions of community safety, using structural equation modeling (SEM) conceptualized by syndemic theory. This study used survey data collected from a county wide sample of middle and high school students (N=25,147) in West Central Florida in 2015. The outcome variable was youth’s perceptions of community safety. Predictors were latent individual and community factors constructed from 14 observed variables including gun accessibility, substance use, depressive symptoms, and multiple neighborhood disadvantage questions. Three structural equation models were conceptualized based on syndemic theory and analyzed in Mplus 8 using weighted least squares (WLS) estimation. Each model’s goodness of fit was assessed. Approximately seven percent of youth reported feeling unsafe in their community. After model modifications, the final model showed a good fit of the data and adhered to the theoretical assumption. In the final SEM model, an individual latent factor was implied by individual predictors measuring gun accessibility without adult’s permission (β=0.70), sadness and hopelessness (β=0.52), alcohol use (β=0.79), marijuana use (β=0.94), and illegal drug use (β=0.77). Meanwhile, a community latent factor was indicated by multiple community problems including public drinking (β=0.88), drug addiction (β=0.96), drug selling (β=0.97), lack of money (β=0.83), gang activities (β=0.90), litter and trash (β=0.79), graffiti (β=0.91), deserted houses (β=0.86), and shootings (β=0.93). A second-order syndemic factor that represented the individual and community factors showed a very strong negative association with youth’s safe perception (β=-0.98). This study indicates that individual risk factors and disadvantaged community conditions interacted with each other and mutually affected youth’s perceptions of community safety. To reduce these co-occurring effects and improve safe perceptions among youth, researchers and practitioners should develop and implement comprehensive strategies targeting both individual and community factors.

scholarly journals COVID-19 Risk Factors, Economic Factors, and Epidemiological Factors nexus on Economic Impact: Machine Learning and Structural Equation Modelling Approaches

2021 ◽  
pp. 395-405
Author(s):  
David Opeoluwa Oyewola ◽  
Emmanuel Gbenga Dada ◽  
Juliana Ngozi Ndunagu ◽  
Terrang Abubakar Umar ◽  
Akinwunmi S.A
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Structural Equation Modeling ◽  
Latent Variables ◽  
Structural Equation ◽  
Equation Modeling ◽  
Support Vector ◽  
Economic Factors ◽  
Negative Effects ◽  
The Impact

Since the declaration of COVID-19 as a global pandemic, it has been transmitted to more than 200 nations of the world. The harmful impact of the pandemic on the economy of nations is far greater than anything suffered in almost a century. The main objective of this paper is to apply Structural Equation Modeling (SEM) and Machine Learning (ML) to determine the relationships among COVID-19 risk factors, epidemiology factors and economic factors. Structural equation modeling is a statistical technique for calculating and evaluating the relationships of manifest and latent variables. It explores the causal relationship between variables and at the same time taking measurement error into account. Bagging (BAG), Boosting (BST), Support Vector Machine (SVM), Decision Tree (DT) and Random Forest (RF) Machine Learning techniques was applied to predict the impact of COVID-19 risk factors. Data from patients who came into contact with coronavirus disease were collected from Kaggle database between 23 January 2020 and 24 June 2020. Results indicate that COVID-19 risk factors have negative effects on epidemiology factors. It also has negative effects on economic factors.

Distress after a Single Violent Crime: How Shame-Proneness and Event-Related Shame Work Together as Risk Factors for Post-Victimization Symptoms

2011 ◽  
Vol 109 (1) ◽  
pp. 3-23 ◽  
Author(s):  
Olof Semb ◽  
Lotta M.J. Strömsten ◽  
Elisabet Sundbom ◽  
Per Fransson ◽  
Mikael Henningsson
Keyword(s):  
Risk Factors ◽  
Violent Crime ◽  
Structural Equation ◽  
Equation Modeling ◽  
Mediating Role ◽  
Shame Proneness ◽  
Shame And Guilt ◽  
Potential Risk Factors ◽  
Guilt Proneness

To increase understanding of post-victimization symptom development, the present study investigated the role of shame- and guilt-proneness and event-related shame and guilt as potential risk factors. 35 individuals ( M age = 31.7 yr.; 48.5% women), recently victimized by a single event of severe violent crime, were assessed regarding shame- and guilt-proneness, event-related shame and guilt, and post-victimization symptoms. The mediating role of event-related shame was investigated with structural equation modeling (SEM), using bootstrapping. The guilt measures were unrelated to each other and to post-victimization symptoms. The shame measures were highly intercorrelated and were both positively correlated to more severe post-victimization symptom levels. Event-related shame as mediator between shame-proneness and post-victimization symptoms was demonstrated by prevalent significant indirect effects. Both shame measures are potent risk factors for distress after victimization, whereby part of the effect of shame-proneness on post-victimization symptoms is explained by event-related shame.

Influence of perceived risks on the decision to invest in equity crowdfunding: a study of Malaysian investors

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shaista Wasiuzzaman ◽  
Lee Lee Chong ◽  
Hway Boon Ong
Keyword(s):  
Risk Factors ◽  
Structural Equation ◽  
Positive Influence ◽  
Equation Modeling ◽  
Investment Risk ◽  
Content Type ◽  
Legal Risk ◽  
Equity Crowdfunding ◽  
Start Ups ◽  
The Relationship

Purpose This study aims to investigate the influence of various risk factors, specifically investment risk, legal risk and technology risk, on the decision of investors to invest in equity crowdfunding ventures in Malaysia. Design/methodology/approach A total of 169 valid responses out of a total of 195 questionnaires were distributed to individuals with prior knowledge of equity crowdfunding. The data from the responses are used to test the relationships using structural equation modeling partial least squares (SEM-PLS). Findings Investigation into the influence of risk factors on the willingness to support equity crowdfunding shows that investment risk and legal risk significantly influence the decision to support equity crowdfunding ventures, but technology risk does not. However, while the influence of investment risk is negative, legal risk is found to have a positive influence. Originality/value This study is important as, to the authors’ knowledge, this is the first study to empirically test the relationship between the various risks inherent in equity crowdfunding investments and the decision to invest. The study is also important to entrepreneurs and start-ups as it provides evidence that while the equity crowdfunding investment community follows the norms of investment, i.e. lower risk is preferred, stricter laws and regulations governing equity crowdfunding may not be needed or may only be relevant in countries where there are more retail, unsophisticated investors.

The interplay between binge eating risk factors: Toward an integrated model

2020 ◽  
pp. 135910532094780
Author(s):  
Katrin Kukk ◽  
Kirsti Akkermann
Keyword(s):  
Risk Factors ◽  
Body Weight ◽  
Negative Affect ◽  
Binge Eating ◽  
Ecological Momentary Assessment ◽  
Structural Equation ◽  
Community Sample ◽  
Equation Modeling ◽  
Ecological Momentary ◽  
Momentary Assessment

We aimed to assess the interplay between dietary restraint and emotion regulation (ER) difficulties as well as other well-known risk factors of binge eating in a community sample of women. Altogether 96 women (mean age 21.5 years; mean BMI 21.7) participated in the study using ecological momentary assessment. Structural equation modeling indicated that restraint and ER pathways are related yet operate independently in predicting binge eating in a unified model. ER difficulties moderated the effect of negative affect and fluctuations in negative affect in predicting binge eating while Neuroticism and preoccupation with body weight predicted binge eating indirectly.

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